| 摘 要: 针对基本型蚁群算法迭代次数多，搜素时间较长，收敛速度慢的缺陷，采用改进的自适应蚁群算法，根据 全局最优解的分布情况自适应地进行信息素范围的更新，从而动态地调整各路径上的信息素强度，同时，建立数学模 型，给出求解TSP问题的改进算法，仿真出通过改进的自适应蚁群算法得到的最优路径，应用到患者位置与急救调度站 之间最优路径的选择。结果表明，该模型和算法在收敛速度和迭代次数上均优于基本型蚁群算法。 |
| 关键词: 自适应蚁群算法；迭代次数；收敛速度；最优路径 |
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中图分类号: TP312
文献标识码: A
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| Application of Emergency Vehicles Scheduling Based on Adaptive Ant Colony Algorithm |
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ZHOU Guiyu，ZHANG Tong
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( Yibin University, Yibin 644007, China)
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| Abstract: In view of the defects from the basic ant colony algorithm frequent iterations and slow speed in convergence,the solution in this paper are using improved adaptive ant colony algorithm,setting up mathematical model,simulating out the optimal path through improved adaptive ant colony algorithm and applying to the choice of the optimal path between emergency dispatching station and the patients' position.The results show that the model and algorithm in convergence speed and the number of iterations are better than the basic ant colony algorithm. |
| Keywords: adaptive ant colony algorithm;iterations;the rate of convergence;the optimal path |
